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219 articles for “Electric Machine”
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Design and Development of Multifunctional Stretcher
Abstract: Hospital stretchers and wheelchairs are integrated in this piece. Instead of using the chair and stretcher individually, the suggested stretcher can be utilized for multiple purposes. Patients' mobility issues can be greatly reduced by this arrangement. There is a challenge in the ICU moving seriously damaged or fractured patients from stretcher to wheelchair. This product is capable of addressing such situations. One more advantage of the proposed design to conduct …
Published in International Journal of Industrial and Product Design Engineering · Vol. 4, Issue 1, 2026 · pp. 29–34 Read article
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IoT Based Electricity Theft Detection System
Abstract: The proliferation of smart grids and advanced metering infrastructure has paved the way for innovative solutions to tackle the longstanding issue of electricity theft. This study presents an IoT-based electricity theft detection system that leverages real-time data analytics and machine learning algorithms to identify potential theft cases. The proposed system utilizes smart meters to collect electricity consumption data, which is then transmitted to a central server for analysis. The system …
Published in Journal of Semiconductor Devices and Circuits · Vol. 12, Issue 2, 2025 · pp. 18–22 Read article
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Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence
Abstract: The increasing demand for sustainable and autonomous environmental monitoring systems has motivated the development of biologically integrated sensing technologies that combine living organisms with advanced cybernetic intelligence. This study proposes a novel framework of Photosynthetic Living Plant–Integrated Cybernetic Sensors for Autonomous Environmental Intelligence, where living plants act as self-sustaining sensing platforms capable of continuously monitoring environmental conditions without external energy sources. By integrating bioelectrical signal acquisition modules, flexible nanomaterial electrodes, …
Published in Recent Trends in Sensor Research & Technology · Vol. 13, Issue 2, 2026 Read article
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Using Machine Learning to Guess Photochemical Reaction Pathways
Abstract: Photochemical reactions are crucial to many activities in the fields of energy conversion, environmental cleanup, and synthetic chemistry. However, predicting their causes and results effectively is still very hard since they entail excited electronic states, nonadiabatic transitions, and complicated potential energy surfaces. Machine learning (ML) has been a powerful technique to go along with classic quantum chemistry methods in the last few years. It offers better prediction capability and lower …
Published in International Journal of Photochemistry and Photochemical Research · Vol. 3, Issue 2, 2025 · pp. 01–12 Read article
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Nanofluids: Advanced Synthesis Methods, Innovative Applications, and Future Directions
Abstract: Nanofluids, a novel mixture of nanoparticles and base fluids, is an innovative blend that has appeared as a transformative advancement in heat transfer and thermal management technologies. This study is going to discuss advanced synthesis methods, properties, and extensive applications of nanofluids in various fields, such as biomedical engineering, electronics cooling, solar energy, and machining. Optimization techniques such as nanoparticle selection, concentration control, and computational fluid dynamics modelling are also …
Published in Journal of Nuclear Engineering & Technology · Vol. 15, Issue 1, 2025 · pp. 1–11 Read article
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The Effects of Energy Consumption on the Turning Process for Various Work-Piece Materials
Abstract: The study modified its goal to energy-intensive titanium alloys, contrasting traditional and high-speed machining processes. According to the study, a solution is needed to reduce or optimize energy use. So, a machined component energy footprint model was created. Several cutting speeds were used to calculate (k). Material removal rates were compared to cutting speeds for a range of materials and levels of detail. A strategy for selecting optimal cutting conditions …
Published in Journal of Polymer & Composites · Vol. 12, Issue 4, 2024 · pp. 54–65 Read article
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A Machine learning approach to asses carbon emission, utility to produce biomaterial
Abstract: The transportation sector, and the automotive industry in particular, has grown significantly over the last ten years. However, these quick advancements have also brought about important problems that require workable answers. The problem of carbon emission is responsible for global warming due to greenhouse gas emission. The present work is focused on CO2 emission from public and personal transport within Agra city on a real-time basis. In the context of …
Published in International Journal of Advanced Control and System Engineering · Vol. 3, Issue 1, 2025 · pp. 22–30 Read article
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Stiffness Optimization of Control Unit of Vehicle Using Vibration Technique
Abstract: All modern automotive engines are controlled by an ECU. Engine efficiency, combustion, and emission characteristics are all affected by ECU tuning or tune-up. The electrical system in automobiles has evolved over time, and it now incorporates automatic machine control of automotive mechanics. In the beginning, a car’s electrical system consisted solely of primitive wiring technologies for supplying power to other parts of the vehicle. Engine management design specifications for the …
Published in Journal of Automobile Engineering and Applications Read article
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Machine Learning-Based Quantification of Polymer Structure Property Relationships for Predictive Material Design
Abstract: Polymer structures exhibit complex, hierarchical arrangements that strongly influence macroscopic properties, yet consistent quantification remains challenging due to nonlinear interactions and limited unified modeling strategies. Existing approaches inadequately capture generalized structure–property mappings across diverse polymer systems. This research aims to establish a machine learning-based quantification model for polymer structure–property relationships to support predictive material design. A Polymer Structure Property Dataset of 5,000 polymer samples includes structural descriptors and experimentally measured …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 737–754 Read article
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Kinetic Power Gyms for Revolutionizing Fitness
Abstract: We are constantly looking for ways to make our lives more sustainable, from reducing our carbon footprint to conserving energy. But what if your workout could contribute to a more sustainable future? Enter the Kinetic Gym, a concept that aims to harness the kinetic energy generated by gym-goers and convert it into usable electricity. The idea is simple: traditional exercise machines, like stationary bikes, treadmills, and elliptical trainers, generate significant …
Published in Journal of Telecommunication, Switching Systems and Networks · Vol. 12, Issue 2, 2025 · pp. 13–21 Read article
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Microstructural and Mechanical characterization of Brass and Bronze alloys
Abstract: Brass, a copper and zinc alloy, is renowned for its malleability and resistance to corrosion, which makes it perfect for musical instruments and plumbing. Aluminium bronze, containing copper and aluminium, offers superior strength and wear resistance, commonly used in marine and industrial applications for its durability and corrosion resistance. This study aimed to compare the micro and macro structural characteristics of brass and aluminium bronze alloys. The microstructures of these …
Published in Journal of Materials & Metallurgical Engineering · Vol. 14, Issue 2, 2024 · pp. 28–37 Read article
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Environmental Impact Assessment of Ocean Energy Converters Using Quantum Machine Learning
Abstract: The accelerating deployment of ocean energy converters (OECs) across tidal, wave, osmotic, and thermal domains necessitates rigorous, data-intensive environmental impact assessment (EIA) frameworks capable of modelling multi-stressor marine ecosystems in real time. Classical machine learning approaches, while operationally mature, encounter scalability bottlenecks and feature correlation limitations when applied to the high-dimensional, non-linear datasets characteristic of offshore monitoring networks. This paper presents a comprehensive quantum machine learning (QML) framework for the …
Published in Journal of Energy, Environment & Carbon Credits · Vol. 16, Issue 1, 2026 · pp. 22–31 Read article
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Smart Material–Based Energy Conversion and Storage Solutions in Industrial Engineering Systems
Abstract: A revolutionary step for attaining energy-efficient, sustainable, and intelligent industrial processes is the use of smart materials with industrial engineering systems. Advanced approaches to energy harvesting, conversion, and storage in industrial settings are made possible via smart materials, which are distinguished by their capacity to sense and react dynamically to mechanical, thermal, electrical, and external cues. These materials enable accurate energy recovery from vibrations in machinery, operational loads, waste heat, …
Published in International Journal of Industrial and Product Design Engineering · Vol. 3, Issue 2, 2025 · pp. 33–38 Read article
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Captive Energy Generation by Using Gym Equipment
Abstract: This project aims to create a sustainable energy source by converting exercise equipment into devices capable of generating electrical power. Traditionally, the mechanical energy produced during workouts is wasted as it dissipates within exercise machines. This project aims to capture and convert that otherwise unused energy into usable electricity. By integrating an alternator-based system into fitness equipment, the mechanical motion generated by users during exercise can be transformed into electrical …
Published in Journal of Microwave Engineering and Technologies · Vol. 12, Issue 3, 2025 · pp. 21–26 Read article
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Identifying and Implementing a Machine Learning Model Suitable for Processing Visually Evoked Potential
Abstract: A Brain-Computer Interface (BCI) is a system that translates brain activity patterns into computer commands, bypassing physical movement. Electroencephalography (EEG) is commonly used to acquire signals in BCI research. Visual evoked potentials (VEPs) are brain responses in the visual cortex to visual stimuli. Recent studies show that exposing individuals to flickering at a consistent frequency generates EEG signals synchronized with the stimulation. Efficient extraction of VEP signals begins with preprocessing …
Published in Journal of Microwave Engineering and Technologies · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Predicting Dielectric Constants of Polymers Using Molecular Structural Descriptors and Explainable Machine Learning: A Data-Driven Approach
Abstract: Accurate prediction of dielectric constants in polymeric materials is fundamental to the rational design of advanced electronic components, energy storage capacitors, flexible substrates, and high-frequency communication circuits. Conventional approaches to identifying suitable polymer dielectrics rely on extensive experimental synthesis and characterisation, which are both time-consuming and resource-intensive. In this work, an explainable machine learning framework is developed to predict the dielectric constant of polymers directly from molecular structural descriptors derived …
Published in Journal of Polymer & Composites · Vol. 14, Issue 3, 2026 · pp. 297–304 Read article
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Enhancing Smart Grid Security: Machine Learning Approaches for Detecting Anomalies
Abstract: The integration of Information and Communication Technology (ICT) with traditional electric grids has led to the development of smart grids. However, this integration has also increased the risk of anomalies, such as cyber-attacks, metering fraud, electricity theft etc. False Data Injection Attacks are a class of cyber-attacks against power grid monitoring systems, where adversaries can inject false data to manipulate the grid’s operation. Metering frauds pertain to malicious customers com- …
Published in Trends in Electrical Engineering · Vol. 14, Issue 2, 2024 · pp. 10–19 Read article
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The Integration of Machine Learning in VLSI IC Design
Abstract: It represents the first use of AI in the domain of integrating circuits, which has been impacted by it. The conventional VLSI design process that is now in use is replaced by this technology. The laborious manual concepts created by people have been replaced with automated design innovations. This development would trigger a profound change in the fields of AI education and hardware computation. With the introduction of contemporary chips, …
Published in Trends in Machine design · Vol. 11, Issue 2, 2024 · pp. 1–8 Read article
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Polymer Nanocomposites and Functional Materials for Lithium-Ion Battery Supercapacitor Hybrid Energy Storage Systems: Materials, Interfaces, and Performance Perspectives
Abstract: The growing need for high-performance energy storage solutions in electric vehicles, renewable energy applications, portable electronics, and other sectors has accelerated research and development efforts in Lithium-Ion Battery–Supercapacitor Hybrid Energy Storage Systems (HESS). By combining the high energy density of lithium-ion batteries with the high power density and fast charge/discharge characteristics of supercapacitors, HESS offers a promising approach to meeting diverse energy storage requirements. Nevertheless, several critical challenges remain that …
Published in Journal of Polymer & Composites · Vol. 14, Issue 4, 2026 · pp. 96–113 Read article
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Advanced AI based Energy Monitoring and Demand Prediction with Theft Detection
Abstract: This paper presents a study on an AI-based energy management system, which is designed for real-time monitoring of energy consumption for theft detection and energy demand prediction. Our energy management system has voltage and current sensors for energy consumption measurement and provides real- time data on voltage (V), current (mA), and energy units. We have implemented Machine Learning algorithm SVM to improve the process of theft detection by identifying anomalies …
Published in Journal of Alternate Energy Sources & Technologies · Vol. 17, Issue 1, 2026 Read article